检索结果-内蒙古大学图书馆

Aggregate 2024年第4期5卷 74-95页

作者： Menglan Lv Junhua Huang Xuanyan Luo Shan Yu Xu Wang Zhuo Wang Fei Pan Bin Zhang Liming Ding Engineering Research Center for Energy Conversion and Storage Technology of Guizhou School of Chemistry and Chemical EngineeringGuizhou UniversityGuiyangChina College of Big Data and Information Engineering Guizhou UniversityGuiyangChina School of Chemical Engineering Guizhou Institute of TechnologyGuiyangChina Center for Excellence in Nanoscience(CAS) Key Laboratory of Nanosystem and Hierarchical Fabrication(CAS)National Center for Nanoscience and TechnologyBeijingChina

Organic solar cells(OSCs)have attracted much interest in the past few decades because of their advantages,such as being lightweight,low cost,simple preparation process,and environmental *** researchers have made significant progress on the active layer materials of OSCs,the interface engineering is another entry point for upgrading the photovoltaic performance of ***,the interface modification materials,including anode interfacial materials and cathode interfacial materials,are two essential parts of interfacial layers for OSCs,in which the excellent interfacial materials can realize the very high-performance photovoltaic *** these interfacial materials,the anode interfacial layers(AILs)play a crucial role in improving photovoltaic *** review expresses a detailed conclusion of the development of anode interfacial materials and an outlook on future trends for OSCs.

关键词： anode interfacial materials organic solar cells power conversion efficiency

来源：评论

学校读者我要写书评

暂无评论

Privacy-Preserving Fingerprint Recognition via Federated Adaptive Domain Generalization

引用

Computers, Materials & Continua 2025年第3期82卷 5035-5055页

作者： Yonghang Yan Xin Xie Hengyi Ren Ying Cao Hongwei Chang Henan Key Laboratory of Big Data Analysis and Processing Computer and Information EngineeringHenan UniversityKaifeng475004China College of Information Science and Technology Nanjing Forestry UniversityNanjing210037China Henan Branch China Life Insurance Co.Ltd.Zhengzhou450000China

Fingerprint features,as unique and stable biometric identifiers,are crucial for identity ***,traditional centralized methods of processing these sensitive data linked to personal identity pose significant privacy risks,potentially leading to user data *** Learning allows multiple clients to collaboratively train and optimize models without sharing raw data,effectively addressing privacy and security ***,variations in fingerprint data due to factors such as region,ethnicity,sensor quality,and environmental conditions result in significant heterogeneity across *** heterogeneity adversely impacts the generalization ability of the global model,limiting its performance across diverse *** address these challenges,we propose an Adaptive Federated Fingerprint Recognition algorithm(AFFR)based on Federated *** algorithm incorporates a generalization adjustment mechanism that evaluates the generalization gap between the local models and the global model,adaptively adjusting aggregation weights to mitigate the impact of heterogeneity caused by differences in data quality and feature ***,a noise mechanism is embedded in client-side training to reduce the risk of fingerprint data leakage arising from weight disclosures during model *** conducted on three public datasets demonstrate that AFFR significantly enhances model accuracy while ensuring robust privacy protection,showcasing its strong application potential and competitiveness in heterogeneous data environments.

关键词： Fingerprint recognition privacy protection federated learning adaptive weight adjustment

来源：评论

学校读者我要写书评

暂无评论

Application of U-Net and Optimized Clustering in Medical Image Segmentation:A Review

引用

Computer Modeling in engineering & Sciences 2023年第9期136卷 2173-2219页

作者： Jiaqi Shao Shuwen Chen Jin Zhou Huisheng Zhu Ziyi Wang Mackenzie Brown School of Physics and Information Engineering Jiangsu Second Normal UniversityNanjing211200China State Key Laboratory of Millimeter Waves Southeast UniversityNanjing210096China Jiangsu Province Engineering Research Center of Basic Education Big Data Application Nanjing211200China School of Data Science Perdana UniversitySerdangSelangor43400Malaysia

As a mainstream research direction in the field of image segmentation,medical image segmentation plays a key role in the quantification of lesions,three-dimensional reconstruction,region of interest extraction and so *** with natural images,medical images have a variety of ***,the emphasis of information which is conveyed by images of different modes is quite *** it is time-consuming and inefficient to manually segment medical images only by professional and experienced ***,large quantities of automated medical image segmentation methods have been ***,until now,researchers have not developed a universal method for all types of medical image *** paper reviews the literature on segmentation techniques that have produced major breakthroughs in recent *** the large quantities of medical image segmentation methods,this paper mainly discusses two categories of medical image segmentation *** is the improved strategies based on traditional clustering *** other is the research progress of the improved image segmentation network structure model based on *** power of technology proves that the performance of the deep learning-based method is significantly better than that of the traditional *** paper discussed both advantages and disadvantages of different algorithms and detailed how these methods can be used for the segmentation of lesions or other organs and tissues,as well as possible technical trends for future work.

关键词： Medical image segmentation clustering algorithm U-Net

来源：评论

学校读者我要写书评

暂无评论

Metal−support interaction in single-atom electrocatalysts:A perspective of metal oxide supports

引用

eScience 2024年第5期4卷 1-9页

作者： Ce Han Shaoqing Zhang Huimin Zhang Yining Dong Pengfei Yao Yingnan Du Ping Song Xue Gong Weilin Xu State Key Laboratory of Electroanalytical Chemistry Jilin Province Key Laboratory of Low Carbon Chemical PowerChangchun Institute of Applied ChemistryChinese Academy of Sciences5625 Renmin StreetChangchunJilin 130022China School of Applied Chemistry and Engineering University of Science and Technology of ChinaHefeiAnhui 230026China

The discovery of single-atom catalysts(SACs)represents a groundbreaking advancement in the field of catalysis over the past *** the in-depth exploration of relevant structure-activity relationships,the metal−support interaction(MSI)is widely adopted to elucidate variations in electronic structure and coordination configuration of atomic active sites on various kinds of ***,we briefly summarize the metal oxide supports for SACs fabrication,including the distinctive characteristics of metal oxide supports,enlightening advancements in metal oxide support-based SACs(MO-SACs),feasible preparation methods for MO-SACs and effective regulation strategies of MSI effect in *** addition,we present our viewpoints and outlook in this field to stimulate rational design and construction of novel MO-SACs applied in diverse renewable energy devices,while some universal suggestions are sincerely given to provoke thoughtful considerations during the research process.

关键词： Single-atom catalyst Metal oxide Electrocatalysis Metal-support interaction

来源：评论

学校读者我要写书评

暂无评论

Superclass Learning with Representation Enhancement

Superclass Learning with Representation Enhancement

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Zeyu Gan Suyun Zhao Jinlong Kang Liyuan Shang Hong Chen Cuiping Li Key Lab of Data Engineering and Knowledge Engineering of MOE Renmin University of China Beijing China Renmin University of China Beijing China

In many real scenarios, data are often divided into a handful of artificial super categories in terms of expert knowledge rather than the representations of images. Concretely, a superclass may contain massive and various raw categories, such as refuse sorting. Due to the lack of common semantic features, the existing classification techniques are intractable to recognize superclass without raw class labels, thus they suffer severe performance damage or require huge annotation costs. To narrow this gap, this paper proposes a superclass learning framework, called SuperClass Learning with Representation Enhancement(SCLRE), to recognize super categories by leveraging enhanced representation. Specifically, by exploiting the self-attention technique across the batch, SCLRE collapses the boundaries of those raw categories and enhances the representation of each superclass. On the enhanced representation space, a superclassaware decision boundary is then reconstructed. Theoretically, we prove that by leveraging attention techniques the generalization error of SCLRE can be bounded under superclass scenarios. Experimentally, extensive results demonstrate that SCLRE outperforms the baseline and other contrastive-based methods on CIFAR-100 datasets and four high-resolution datasets.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Fine-Grained Anomaly Detection on Dynamic Graphs via Attention Alignment 40

Fine-Grained Anomaly Detection on Dynamic Graphs via Attenti...

引用

40th IEEE International Conference on data engineering, ICDE 2024

作者： Chen, Dong Zhao, Xiang Xiao, Weidong National University of Defense Technology National Key Laboratory of Information Systems Engineering China National University of Defense Technology Laboratory for Big Data and Decision China

ISBN: (纸本)9798350317152

Dynamic graphs are ubiquitous in our lives, yet they are also susceptible to the risks imposed by malicious activities. However, identifying anomalies in these dynamic graphs presents a challenging task due to the complex graph structures. Existing methods for dynamic anomaly detection primarily focus on learning representations for each timestamp and using sequence modeling techniques to capture and model the temporal information. Despite extensive research, dynamic anomaly detection still faces two key challenges. First, existing methods are limited in effectively using fine-grained temporal information. Second, they have limited generalization capabilities under unsupervised settings. Overcoming these challenges is crucial for advances in dynamic anomaly detection. In this paper, we propose a novel unsupervised anomaly detection method for dynamic graphs. Our approach leverages complex temporal information through fine-grained sampling and embedding modules. Additionally, we introduce an attention alignment strategy to minimize discrepancies in contextual attention between source and target nodes. Through a comprehensive evaluation, we demonstrate that our strategy effectively mitigates overfitting and improves generalization. Experiments on ten dynamic graph datasets validate the effectiveness of our proposed method in detecting anomalies. © 2024 IEEE.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Research on Pedestrian Gender Detection Based on A Lightweight Model 36

Research on Pedestrian Gender Detection Based on A Lightweig...

引用

36th Chinese Control and Decision Conference, CCDC 2024

作者： Yuling, Hu Xinyi, Wang Weiguang, Zou Beijing University Of Civil Engineering And Architecture Institute Of Electrical And Information Engineering China Beijing University Of Civil Engineering And Architecture Beijing Key Laboratory Of Intelligent Processing For Building Big Data Beijing China

ISBN: (纸本)9798350387780

In recent years, a variety of emergency events have been occurring in buildings in countries. For there are some differences between male and female in movement ability and evacuation behavior, gender has a non-negligible impact on evacuation and decision-making of emergency events. Thus, it is of great practical significance to detect the gender of pedestrians at entrances or exits of buildings in real time to grasp the proportion of different gender people in buildings and to formulate emergency warning or evacuation strategies scientifically. In response to the requirement of rapid emergency response, this paper proposes a pedestrian gender detection method based on a lightweight object detection model YOLOX-Tiny. In addition, considering the inaccurate pedestrian gender detection caused by the change of pedestrian posture and camera angle, the attention mechanism CBAM is introduced to enhance the ability of filtering a large amount of redundant information, obtaining key information and acquiring pedestrian gender characteristic information. Through the experiments of self-made pedestrian gender datasets, the results show that the detection accuracy of the improved model is increased by 1.8%, and the detection speed reaches 251FPS, which can meet both speed and accuracy of pedestrian gender detection in emergencies. © 2024 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Multiparameter sensor based on the long-period fiber gratings inscribed in a pre-twisted polarization-maintaining fiber

引用

IEEE Sensors Journal 2025年第11期25卷 19315-19322页

作者： Chen, Siyu Jiang, Chen Ma, Yuehui Fan, Xiaolong Zhao, Yunhe Mou, Chengbo Liu, Yunqi Shanghai University Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai Institute for Advanced Communication and Data Science School of Communication and Information Engineering 99 Shangda Road Shanghai200444 China Nanjing210023 China Shanghai Maritime University Institute of Logistics Science and Engineering Shanghai201306 China

We demonstrate the fabrication of pre-twisted long-period fiber gratings (PT-LPFGs) in polarization-maintaining fibers (PMFs) using a CO2 laser. This technique leverages pre-twisted fibers combined with laser exposure, eliminating the need for precise alignment along the PMF axis, a key limitation of conventional single-side CO2 laser methods. The PT-LPFGs with the periods of 420 to 480 μm were successfully fabricated, achieving a maximum polarization-dependent loss (PDL) exceeding 20 dB at the resonance wavelength. The dual-dips resonance of the LP11 core mode was observed in the 1.0 μm wavelength band. Further chemical etching was applied to adjust the cladding mode resonance wavelength near the dispersion turning point (DTP). This adjustment enabled dual-dips resonance with LP14 and LP15 cladding modes along the PMF’s slow and fast axes, respectively, within the 2.0 μm wavelength band. The sensing performance of PT-LPFGs near the DTP was evaluated. Experimental results demonstrate that these gratings exhibit a high sensitivity of up to 14100 nm/RIU for the surrounding refractive index range of 1.448 to 1.457. Furthermore, the temperature and strain sensitivities were measured to be at 713 pm/°C and -49.4 pm/μΕ, respectively. These findings highlight the potential of PT-LPFGs for high-sensitivity fiber sensors, PDL compensators, and other advanced optical applications. © 2001-2012 IEEE.

关键词： Polarization-maintaining fiber

来源：评论

学校读者我要写书评

暂无评论

Edge-Driven Industrial Computing Power Networks: Digital Twin-Empowered Service Provisioning by Hybrid Soft Actor-Critic

引用

IEEE Transactions on Vehicular Technology 2025年第5期74卷 8095-8109页

作者： Zhang, Long Song, Deng-Ao Zhang, Hongliang Tian, Ni Zhuang, Zirui Niyato, Dusit Han, Zhu Hebei University of Engineering School of Information and Electrical Engineering Handan056038 China Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Nanyang Technological University College of Computing and Data Science 639798 Singapore University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

With the proliferation of data-intensive industrial applications, the collaboration of computing powers among standalone edge servers is vital to provision such services for smart devices. In this paper, we propose an edge-driven industrial computing power network (CPN) by orchestrating the computing and network resources of edge servers through the centralized resource scheduling and decentralized task computing. However, efficient task offloading and collaborative processing is challenging, which requires higher degrees of network automation and intelligence. Therefore, we incorporate digital twins (DTs) into the edge-driven CPN architecture, where the DTs are created as the digital replicas to assist both the computation offloading and collaborative processing. A joint optimization problem of the computing power assignment, service association, task partition, and transmit power control is formulated for maximizing the system average weighted utility. Due to the temporal-spatial variability of tasks and the resulted dynamic environment, we transform the original problem as a Markov decision process aiming at maximizing the long-term average weighted utility. To efficiently handle the high-dimensional discrete-continuous action space, a hybrid soft actor-critic based deep reinforcement learning algorithm is developed for optimizing the joint design. Simulation results validate the superiority of our proposed algorithm over the benchmarks, showing the significant gains obtained by integrating DTs into the edge-driven CPN. © 1967-2012 IEEE.

关键词： Markov processes

来源：评论

学校读者我要写书评

暂无评论

Blockchain-Empowered Asynchronous Federated Reinforcement Learning for IoT-Based Traffic Trajectory Prediction

引用

IEEE Internet of Things Journal 2025年第11期12卷 17095-17109页

作者： Wang, Bin Tian, Zhao Tang, Fengxiao Pan, Heng She, Wei Liu, Wei Zhengzhou University School of Computer and Artificial Intelligence Zhengzhou450002 China Zhengzhou University School of Cyber Science and Engineering Zhengzhou450002 China Central South University School of Computer Science and Engineering Changsha410083 China Zhongyuan University of Technology School of Cyber Space Security Zhengzhou450007 China Zhengzhou University School of Cyber Science and Engineering Zhengzhou University The Zhengzhou Key Laboratory of Blockchain and Data Intelligence Zhengzhou450002 China

Vehicle trajectory prediction plays a crucial role in IoT-based intelligent transportation systems, which can effectively address key issues such as driving safety and multi-vehicle collaboration. However, the sensitivity of trajectory data and the reluctance of data holders to share it constrain the prediction model's ability to capture vehicle behavior patterns in different scenarios. To address the above problems, we propose a blockchain-enabled asynchronous federated proximal policy optimization framework (BE-AFPPO) for the trajectory prediction of self-driving vehicles. Firstly, we propose a Curiosity Proximal Policy Optimisation (C-PPO) algorithm. The method utilizes a driven exploration strategy to actively motivate the intelligent agent to explore the unknown state space. The avoidance policy model reaches a local optimum when processing trajectory data. In addition, we design historical GRU and future GRU as input layers. The target's historical motion features and future trajectory features are extracted, respectively. Then, various data is received through asynchronous federated learning. This model can fully learn the vehicle's behavior patterns in different scenarios, which improves prediction accuracy. Based on this, we develop a blockchain-based Dynamic Group Practical Byzantine Fault Tolerance (DG-PBFT) consensus algorithm. This enhances the credibility and integrity of the data while enriching the sources of trajectory data. Finally, we perform the experiments on the publicly available dataset nuScenes. The results demonstrate that the proposed method improves the robustness and accuracy of trajectory prediction. © 2014 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：